PulseOn is a wrist-worn optical heart rate (HR) monitor based on photoplethysmography. It utilizes multi-wavelength technology and optimized sensor geometry to monitor blood flow at different depths of skin tissue, and it dynamically adapts to an optimal measurement depth in different conditions. Movement artefacts are reduced by adaptive movement-cancellation algorithms and optimized mechanics, which stabilize the sensor-to-skin contact. In this paper, we evaluated the accuracy and reliability of PulseOn technology against ECG-derived HR in laboratory conditions during a wide range of physical activities and also during outdoor sports. In addition, we compared the performance to another on-the-shelf wrist-worn consumer product Mio LINK(®). The results showed PulseOn reliability (% of time with error <;10bpm) of 94.5% with accuracy (100% - mean absolute percentage error) 96.6% as compared to ECG (vs 86.6% and 94.4% for Mio LINK(®), correspondingly) during laboratory protocol. Similar or better reliability and accuracy was seen during normal outdoor sports activities. The results show that PulseOn provides reliability and accuracy similar to traditional chest strap ECG HR monitors during cardiovascular exercise.

Download full-text PDF

Source
http://dx.doi.org/10.1109/EMBC.2015.7318391DOI Listing

Publication Analysis

Top Keywords

accuracy reliability
8
reliability pulseon
8
optical heart
8
heart rate
8
evaluation accuracy
4
pulseon
4
pulseon optical
4
rate monitoring
4
monitoring device
4
device pulseon
4

Similar Publications

Purpose: Current technologies to define the zone of acute peripheral nerve injury intraoperatively are limited by surgical experience, time, cumbersome electrodiagnostic equipment, and interpreter reliability. In this pilot study, we evaluated a real-time, label-free optical technique for intraoperative nerve injury imaging. We hypothesize that fluorescence lifetime imaging (FLIm) will detect a difference between the time-resolved fluorescence signatures for acute crush injuries versus uninjured segments of peripheral nerves in sheep.

View Article and Find Full Text PDF

Digital muscle reconstructions have gained attraction in recent years, serving as powerful tools in both educational and research contexts. These reconstructions can be derived from various 2D and 3D data sources, enabling detailed anatomical analyses. In this study, we evaluate the efficacy of surface scans in accurately reconstructing the volumes of the rotator cuff and teres major muscles across a diverse sample of hominoids.

View Article and Find Full Text PDF

Mobile Ad Hoc Networks (MANETs) are increasingly replacing conventional communication systems due to their decentralized and dynamic nature. However, their wireless architecture makes them highly vulnerable to flooding attacks, which can disrupt communication, deplete energy resources, and degrade network performance. This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs.

View Article and Find Full Text PDF

Electric vehicles (EVs) rely heavily on lithium-ion battery packs as essential energy storage components. However, inconsistencies in cell characteristics and operating conditions can lead to imbalanced state of charge (SOC) levels, resulting in reduced capacity and accelerated degradation. This study presents an active cell balancing method optimized for both charging and discharging scenarios, aiming to equalize SOC across cells and improve overall pack performance.

View Article and Find Full Text PDF

Nanobody-based indirect competitive ELISA for the detection of aflatoxin M1 in dairy products.

Sci Rep

January 2025

Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, College of Food Science and Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China.

Aflatoxin M1 (AFM1) is known to be carcinogenic, mutagenic, and teratogenic and poses a serious threat to food safety and human health, which makes its surveillance critical. In this study, an indirect competitive ELISA (icELISA) based on a nanobody (Nb M4) was developed for the sensitive and rapid detection of AFM1 in dairy products. In our previous work, Nb M4 was screened from a Bactrian-camel-immunized phage-displayed library.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!